期刊
APPLIED SCIENCES-BASEL
卷 12, 期 6, 页码 -出版社
MDPI
DOI: 10.3390/app12062828
关键词
2D; 3D medical image registration; normalized cross-correlation; differential operator; image processing
类别
资金
- Sichuan Science and Technology Program [2021YFQ0003]
Image-guided surgery (IGS) reduces tissue damage and improves accuracy and targeting of lesions by increasing visual field. This experiment studies a 2D/3D medical image registration algorithm based on gray level and introduces a new similarity measure and a multiresolution strategy to enhance registration accuracy and efficiency.
Image-guided surgery (IGS) can reduce the risk of tissue damage and improve the accuracy and targeting of lesions by increasing the surgery's visual field. Three-dimensional (3D) medical images can provide spatial location information to determine the location of lesions and plan the operation process. For real-time tracking and adjusting the spatial position of surgical instruments, two-dimensional (2D) images provide real-time intraoperative information. In this experiment, 2D/3D medical image registration algorithm based on the gray level is studied, and the registration based on normalized cross-correlation is realized. The Gaussian Laplacian second-order differential operator is introduced as a new similarity measure to increase edge information and internal detail information to solve single information and small convergence regions of the normalized cross-correlation algorithm. The multiresolution strategy improves the registration accuracy and efficiency to solve the low efficiency of the normalized cross-correlation algorithm.
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